_{29th September, 2026}

Our client in NYC is seeking a Senior Data & AI Architect & Engineering Manager to join their team!
 
This is a hybrid/full-time/direct-hire position
Salary range based on experience: Starting at $165K
 
 
Mission
Lead the Data and AI architecture and engineering function as a technical manager with direct accountability for team performance, staffing, talent development, technical direction, and delivery. This is a team leader role that supervises a team of data engineers, analytics engineers, and architects. The role owns Microsoft Fabric architecture, enterprise data and semantic modeling, integration design, and governed AI enablement while building an engaged, capable, and accountable team.
 
Responsibilities:
 
People Leadership, Performance & Team Development (Direct Reports)

• Directly manage and supervise a team of engineers and architects with accountability for hiring, onboarding, goals, performance reviews, development plans, workload allocation, employee relations, succession, and retention.
• Hold regular one-on-ones, set clear expectations, recognize progress, and give balanced, constructive feedback with consistent follow-through.
• Coach engineers and architects through design reviews, code reviews, pairing, delegation, and individual development plans; build bench strength without becoming the sole decision bottleneck.
• Address performance or behavioral gaps promptly and constructively, focusing on facts, impact, expectations, support, and measurable improvement.
• Foster an inclusive, psychologically safe, solution-oriented team culture during ambiguity and delivery pressure.

Microsoft Fabric Architecture & Platform Delivery

• Own the end-to-end Microsoft Fabric reference architecture across OneLake, Lakehouse, Warehouse, Pipelines, Dataflows Gen2, notebooks, Real-Time Intelligence, Power BI, workspaces, domains, and capacities.
• Lead the team delivering foundational Fabric patterns and priority platform components; stay hands-on for high-risk design, prototyping, review, and troubleshooting.
• Define medallion, batch, CDC, streaming, mirroring, shortcut, deployment, security, monitoring, and capacity-management patterns.
• Maintain current architecture diagrams, standards, roadmaps, architecture decisions, and implementation guardrails.

Enterprise Data, Semantic Model & Integration Architecture

• Own conceptual, logical, physical, canonical, dimensional, and enterprise semantic model standards across policy, claims, provider, patient safety, underwriting, actuarial, and finance domains.
• Establish Power BI semantic model standards for measures, calculation groups, naming, certified datasets, reuse, refresh, performance, lineage, ownership, and RLS/OLS/CLS.
• Define data contracts, model versioning, metadata, glossary, master/reference data, ontology, and knowledge-graph alignment.
• Design secure integrations across Fabric, Azure, operational systems, content platforms, and external providers using APIs, events, CDC, streaming, files, and batch patterns.

Engineering Excellence, Governance, Reliability & Cost
 
Establish Git-based delivery, pull-request review, automated testing, CI/CD, environment promotion, release, rollback, observability, incident response, and operational-readiness standards.

• Define service objectives and telemetry for pipelines, capacities, semantic models, AI services, and critical data products; lead root-cause analysis and durable remediation without blame.
• Embed least privilege, secrets management, PHI/PII controls, sensitivity, retention, data quality, lineage, auditability, and responsible AI controls into delivery patterns.
• Forecast, monitor, explain, and optimize platform capacity, compute, storage, licensing, and vendor cost against business value.

Strategic Partnership, Communication & Change Leadership

•  Translate strategy and ambiguous business needs into decision-ready options, recommendations, diagrams, roadmaps, staffing plans, and executable work for technical and executive audiences.
• Partner with Enterprise Architecture, Security, Infrastructure, Governance, Claims, Underwriting, Actuarial, Reporting, Legal/Compliance, Finance, and vendors to resolve tradeoffs and dependencies.
• Communicate risks early with context, impact, options, and a recommended action; represent decisions with composure, transparency, and sound judgment.
• Lead adoption of architecture standards and new ways of working through stakeholder engagement, education, measurement, and reinforcement.

 
 
 
Qualifications:

• People-manager role: 3+ years directly managing and supervising data engineers, analytics engineers, architects, or similar technical staff, including managing a team through change.
• Direct accountability for hiring, onboarding, goal setting, performance reviews, coaching, career development, workload planning, succession planning, employee relations, and retention.
• Bachelor's or master's degree in Computer Science, Data Engineering, Information Systems, Software Engineering, or a related field; equivalent experience considered.
• 10+ years of deep enterprise data, analytics, engineering, or architecture experience with accountability for architecture decisions in production.
• Hands-on expertise with Microsoft Fabric (OneLake, Lakehouse, Warehouse, Pipelines, Dataflows Gen2, notebooks, Real-Time Intelligence, Power BI, workspaces, security, and capacity governance).
• Expertise in enterprise data and semantic modeling: conceptual, logical, physical, dimensional, and canonical models; data contracts; Power BI semantic models; lineage; RLS/OLS/CLS; and performance tuning.
• Strong SQL, Python, PySpark, Delta Lake, batch, CDC, streaming, API, DataOps, automated testing, CI/CD, observability, and cost-management experience.
• Constructive, solution-oriented leadership and strong executive communication; regulated-industry experience (insurance, healthcare, or financial services) preferred.

 
Applicants must be authorized to work in the U.S.
 
We are an equal-opportunity employer. We do not discriminate in hiring or employment against any individual based on race, color, gender, national origin, ancestry, religion, physical or mental disability, age, veteran status, sexual orientation, gender identity or expression, marital status, pregnancy, citizenship, or any other factor protected by anti-discrimination laws.

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